Time: 13:00, June 16, 2026
Venue: Room 503, SEIE Building
Overview:
This study presents a novel Wavelet Transformer Forecasting (WTF) framework for predicting hypersonic glide vehicle (HGV) trajectories with lateral maneuvers. Our approach combines wavelet decomposition with transformer-based sequence modeling to capture both temporal and frequency-domain characteristics of complex HGV trajectories. Experimental results demonstrate significant improvements in prediction accuracy compared to traditional methods, particularly for trajectories with complex maneuvering patterns.
Organizer: School of Artificial Intelligence and Data Science (SAIDS)
Speaker:
Dr. Howard Li (Li Hao) is an IEEE Senior Member and a Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick. He currently serves as IEEE SA Board of Governors (BOG) Member and as Chair IEEE Autonomous Robotics (AuR) Ontology Working Group. He also serves as Co-Chair of IEEE 6G Empowering Robotics Working Group.
